Performance Evaluation of Multi-type Five-axis Machine Tool With Recognizable Performance Evaluation by Fuzzy Theory

Zhang

2022

Preprint

Self Cite

Background: "Subtractive manufacturing" and "additive manufacturing" are inseparable mechanical processing manufacturing processes, and must be carried out at the same time is an established processing concept. In order to achieve continuous improvement, production machine tools are required to effectively identify the causes of possible defects. Therefore, the uncertainty of performance prediction is a very important subject. Methods: Combination of Digital Twin、RPE and VM is used to make the quantized value close to the true overall average value, which can be used with other algorithm theorems. Results: Final Total σ (sigma) represents the σ control value after comparing the DT value of these types of "reduced additive manufacturing" with the experimental value of ET. It shows result of overall additive manufacturing is 53 σ, and Table 5 shows that of overall subtractive manufacturing is 64 σ. It can be evaluate the performance of the concept of adding or subtracting material manufacturing and processing to promote the subsequent development of artificial intelligence (AI).Conclusions: The combined RPE method is not limited to cutting test parts of any geometry, and can be designed that the cutting test parts also collect sufficient statistical data. The detailed information about machine tool analysis considers the advantages and disadvantages of each machine tool. Designers must continue to improve the performance of adding and subtracting materials, and objectively give evaluation qualified performance indicators, in order to continuously correct the improvement and perform performance evaluation.

Section: Literature Reviewmentioning

confidence: 99%

Section: Data Collection and Processingmentioning

confidence: 99%

Use Recognizable Digital twin in Virtual Measurement for General Both Evaluation of Additive & Subtractive Manufacturing Process

Zhang

2022

Preprint

Self Cite

“…In 2019, Chang Han-jui [ 18 ] reviewed various methods for evaluating the performance of five-axis machine tools through identification and multi-type comparison, and RPE was found to be the most practical. RPE is currently one of the research methods that can obtain accurate reference data through quantitative and identification methods, and it is also one of the evaluation methods for multi-type five-axis machine tool methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting of Process Parameters for Theoretical Concentrated Stress of Fatigue Notch Coefficient of Auto Parts Using Virtual Recognizable Performance Evaluation Research

Sun

et al. 2022

Polymers

This paper analyzes the structure of the key parts of the car belt guide, and the average stress of the vulnerable parts is simulated by analysis software. The theoretical stress of the section is calculated. The theoretical stress concentration factor (Kt) is given. The relation between the gap radius and the notch coefficient (Kf) was studied according to a previous Kf calculation formula. The tensile tests of real products are used as reference data. The results showed that Kf and Kt are linear in most cases, but there are also cases of non-compliance. The relationship between the fatigue notch coefficient Kf and the theoretical stress concentration coefficient Kt was closely related to the service life and fatigue strength of the product. In addition, we found that the size and direction of warpage improved significantly with the increase of fillet size, which was not consistent with the effect of adding glass fiber material. The rounded corners of ordinary PP materials usually displayed forward warping, but the addition of glass fiber into PP materials made the degree of warping smaller, or even led to reverse warping. The size of rounded corners is an important optimization parameter. The relationship between Kf and Kt was studied from the perspectives of virtual measurement (VM) and recognizable performance evaluation (RPM). According to abnormal filling pressure, these relationships were compared with filling data to generate a fracture initiation control model. Based on a large amount of normal process data and quality inspection data, the historical data (causes) and quality inspection data (results) were combined.

“…Only by constructing a widely accepted interpretation benchmark can a basic improvement process be established. In 2018-2019, Chang [29,30] obtained accurate reference data using the recognizable performance evaluation (RPE) method and determined the corresponding number (σ-sigma) of the distribution of each measurement region, so this paper attempts to introduce fuzzy theory to obtain excellent research results, then calculate the attribution level of the measured item. By providing a direct differentiation of the defuzzification attribution reduction interval to manage the distribution yield of each frequency distribution, conflicts in test performance evaluation that may occur in various fields can be resolved by directly evaluating the predicted results.…”

Section: Literature Reviewmentioning

confidence: 99%

Using Recognizable Fuzzy Analysis for Non-Destructive Detection of Residual Stress in White Light Elements

Mao

et al. 2021

Applied Sciences

Self Cite

The phenomenon of residual stress in optical lens injection molding affects the quality of optical devices, with the refractive errors that are caused by geometric errors being the most serious, followed by the reduced accuracy and function of optical components; it is very important to ensure that the lens geometry remains intact and that the refractive index is reduced. This paper uses a photoelastic stress compensation method for measurement verification along with fuzzy theory to reorganize a set of processes that can be used to evaluate the residual stress of a product, whereby the use of corresponding theoretical formulas can effectively quantify and measure the residual stress of the product. A mold flow simulation is used to analyze the molded optical components and determine the feasibility of evaluating the quality of the lens. Through the measurement of the refractive stress value of the optical components, the molding quality of the lens can be improved, and its force distribution effects can be investigated. Geometric analysis and shear stress affect the performance of optical components, and these errors may also cause irreparable problems during secondary processing. Therefore, it is crucial to reduce the residual stress of optical components. When the stress distribution is uniform and the internal melting pressure is reasonably configured, the product’s shrinkage rate can be controlled; the method for determining the residual stress is the core theme of this research.